A recent ‘Top Rank' marketing blog entry by Jolina Pettice argues that the use of web analytics packages such as Prospectvision provide an excellent way to enhance marketing efforts, and that combining analytics with User Experience (UX) information may provide even greater advantages. In this context, analytics is defined as telling how visitors are using a website, whereas User Experience research provides insight into the behavior and motivation of visitors.
It is argued that combining analytics with UX provides greater insight into the ‘what and the why' of what's happening on a website. It also allows potential problems relating to a website's navigation or usability to be identified more quickly.
In support of this hypothesis, the example of an insurance quoting website is given. The insurance company was going through a website redesign and decided that it was a good time to double check its online form process. The goal was to identify where on the website's ‘funnel' visitors were getting stuck and abandoning the process. Utilising UX (which in this context could mean simply sitting with web users and witnessing their navigation strategy) in conjunction with analytics enabled comparison of ‘drop off' points - the places on the website identified by users as being confusing or irritating.
With regards the insurance quote website, an obvious ‘drop off' on the website was after the quote was delivered - because it can be expected that some visitors won't like the quote they received and will abandon the website to get a different quote or purchase elsewhere.
However, the real value lay in identifying the unexpected drop-offs: for example, where a user was asked to supply personal or confidential information. One such drop-off point for the health insurance quote form was the request for a social security number. Almost all users are cautious when giving such information online, but the problem in this particular case was that the information was asked for too early in the process, before the person was invested.
As such, they identified an item to test. After placing the request for the social security number further into the funnel where the user was more invested and felt more relaxed about giving personal information, the abandonment rate decreased.
An additional drop-off point on the form was found to be a question relating to where users attended college, which some - via the user experience testing - found offensive and/or didn't understand how it was relevant to an insurance quote. Analytics confirmed this and showed a higher than normal drop-off rate at the point that question was asked in the funnel. The important points to ask are why this question is part of the form, and if it is necessary. If not, it should be removed, in order to improve the percentage of visitors who get further in the funnel and closer to a sale.
In summary, the blog entry summarises six main areas to focus on, combining both Analytics and UX Data in order to improve a website's marketing strategy:
1. Landing Page Optimization
Analytics: Bounce Rate, Conversion Rate
UX: Why people convert.
2. Site Navigation
Analytics: Top Content
UX: How they get there
3. Form Completion
Analytics: Abandonment, Page reloads
UX: Specific Objections
4. Content
Analytics: Time Spent on page
UX: Is it engaging?
5. Testing
Analytics: A/B Testing
UX: What to Test
6. Terminology
Analytics: Search Logs
UX: How people use language - what is your target marking using to search for you
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